Modern manufacturing processes can be complex and intricate. Consumer demands and world-wide competition have driven manufacturing processes to become flexible, adaptive, and cost effective. As a result, the manufacturing processes used to drive and enable production have become increasingly complex. Control logic is the set of specific commands or work instructions given to automated, semi-automated, and manual workstations in a manufacturing process. Known methods to create, implement, and maintain control logic are labor intensive. Control engineers must employ their skills and experience to manually create and edit the data required to generate control logic in order to precisely drive every permutation of the manufacturing process.
Known methods employing control engineers to manually perform the tasks required to create control logic have many drawbacks. The quality of work conducted by a control engineer is dependent upon the competency of the particular engineer. Errors in the control logic generating process can increase the occurrence of undesirable events; cause decreased production, quality, and efficiency; lower customer satisfaction; and increase warranty cost. Limited availability of a qualified engineer to perform adaptations to a manufacturing process may cause delays in implementations of changes or may become a bottleneck to product improvement processes. The labor involved in the programming activities drives up the costs of the manufacturing processes.
Manufacturing processes involving complex mechanical devices are frequently described as discrete manufacturing processes. Optimization of discrete manufacturing processes involves balancing the work assignments within the series of events included in the manufacturing process with other manufacturing concerns such that the desired end product is produced efficiently. Manufacturing concerns addressed in the optimization process include workload balance, equipment availability, operator well being, quality, cost, and throughput or the number of parts produced in a time span. Optimization involves accepting input regarding the priority of the manufacturing concern, analysis of the work to be performed, breaking that work down into the smallest workable units or work elements, and then apportioning that work into work assignments throughout the available workstations based on the priority of the manufacturing concerns. The assembled work assignments are collectively referred to as a sequence of operations. The sequence of operations dictates the task by task process by which the product is manufactured, and the control logic implements the sequence of operations into a set of enabling instructions to each workstation.
Analyzing the work to be performed in a manufacturing process is labor intensive and time consuming. Complicated products such as electronics, vehicles, airplanes, and the like may involve millions of possible interactions between part components and assembly tasks. Carrying information regarding the parts and manufacturing process forward in a compatible, useful format to later comparisons and calculations is a difficult task prone to error and highly dependent on the competency and vigilance of the engineer involved. Further, the task of prioritizing manufacturing concerns and creating a viable sequence of operations for a manufacturing process is a highly intensive and complicated endeavor. The productivity of a manufacturing facility rests heavily on the ability of the facility to implement an efficient sequence of operations. Any method streamlining and error-proofing the process of the generation of a sequence of operations quickly translates to the bottom line of a manufacturing facility.